Residential woodsmoke is an under-regulated source of fine particulate matter (PM2.5), often surpassing mobile and industrial emissions in rural communities in North America and elsewhere. In the province of British Columbia (BC), Canada, many municipalities are hesitant to adopt stricter regulations for residential wood burning without empirical evidence that smoke is affecting local air quality. The objective of this study was to develop a retrospective algorithm that uses 1-h PM2.5 concentrations and daily temperature data to identify smoky days in order to prioritise communities by smoke impacts. Levoglucosan measurements from one of the smokiest communities were used to establish the most informative values for three algorithmic parameters: the daily standard deviation of 1-h PM2.5 measurements; the daily mean temperature; and the daytime-to-nighttime ratio of PM2.5 concentrations. Alternate parameterizations were tested in 45 sensitivity analyses. Using the most informative parameter values on the most recent two years of data for each community, the number of smoky days ranged from 5 to 277. Heat maps visualizing seasonal and diurnal variation in PM2.5 concentrations showed clear differences between the higher- and lower-ranked communities. Some communities were sensitive to one or more of the parameters, but the overall rankings were consistent across the 45 analyses. This information will allow stakeholder agencies to work with local governments on implementing appropriate intervention strategies for the most smoke-impacted communities.

An Aerodyne quadrupole aerosol mass spectrometry (Q-AMS) was utilized to measure the size-resolved chemical composition of non-refractory submicron particles (NR-PM1) from October 27 to December 3, 2014 at an urban site in Lanzhou, northwest China. The average NR-PM1 mass concentration was 37.3 μg m−3 (ranging from 2.9 to 128.2 μg m−3) under an AMS collection efficiency of unity and was composed of organics (48.4%), sulfate (17.8%), nitrate (14.6%), ammonium (13.7%), and chloride (5.7%). Positive matrix factorization (PMF) with the multi-linear engine (ME-2) solver identified six organic aerosol (OA) factors, including hydrocarbon-like OA (HOA), coal combustion OA (CCOA), cooking-related OA (COA), biomass burning OA (BBOA) and two oxygenated OA (OOA1 and OOA2), which accounted for 8.5%, 20.2%, 18.6%, 12.4%, 17.8% and 22.5% of the total organics mass on average, respectively. Primary emissions were the major sources of fine particulate matter (PM) and played an important role in causing high chemically resolved PM pollution during wintertime in Lanzhou. Back trajectory analysis indicated that the long-range regional transport air mass from the westerly was the key factor that led to severe submicron aerosol pollution during wintertime in Lanzhou.

Initiatives to displace petroleum and climate change mitigation have driven a recent increase in space heating with biomass combustion. However, there is ample evidence that biomass combustion emits significant quantities of health damaging pollutants. We investigated the near-source micro-environmental air quality impact of a biomass-fueled combined heat and power system equipped with an electrostatic precipitator (ESP) in Syracuse, NY. Two rooftop sampling stations with PM2.5 and CO2 analyzers were established in such that one could capture the plume while the other one served as the background for comparison depending on the wind direction. Four sonic anemometers were deployed around the stack to quantify spatially and temporally resolved local wind patterns. Fuel-based emission factors were derived based on near-source measurement. The Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model was then applied to simulate the spatial variations of primary PM2.5 without ESP. Our analysis shows that the absence of ESP could lead to an almost 7 times increase in near-source primary PM2.5 concentrations with a maximum concentration above 100 μg m−3 at the building rooftop. The above-ground “hotspots” would pose potential health risks to building occupants since particles could penetrate indoors via infiltration, natural ventilation, and fresh air intakes on the rooftop of multiple buildings. Our results demonstrated the importance of emission control for biomass combustion systems in urban area, and the need to take above-ground pollutant “hotspots” into account when permitting distributed generation. The effects of ambient wind speed and stack temperature, the suitability of airport meteorological data on micro-environmental air quality were explored, and the implications on mitigating near-source air pollution were discussed.

Atmospheric acid deposition is a global environmental issue. China has been experiencing serious acid deposition, which is anticipated to become more severe with the country's economic development and increasing consumption of fossil fuels in recent decades. We explored the spatiotemporal variations of acid deposition (wet acid deposition) and its influencing factors by collecting nationwide data on pH and concentrations of sulfate (SO4²⁻) and nitrate (NO3⁻) in precipitation between 1980 and 2014 in China. Our results showed that average precipitation pH values were 4.59 and 4.70 in the 1990s and 2010s, respectively, suggesting that precipitation acid deposition in China has not seriously worsened. Average SO4²⁻ deposition declined from 40.54 to 34.87 kg S ha⁻¹ yr⁻¹ but average NO3⁻ deposition increased from 4.44 to 7.73 kg N ha⁻¹ yr⁻¹. Specifically, the area of severe precipitation acid deposition in southern China has shrunk to some extent as a result of controlling the pollutant emissions; but the area of moderate precipitation acid deposition has expanded in northern China, associated with rapid industrial and transportation development. Furthermore, we found significant positive correlations between precipitation acid deposition, energy consumption, and rainfall. Our findings provide a relatively comprehensive evaluation of the spatiotemporal dynamics of precipitation acid deposition in China over past three decades, and confirm the idea that strategies implemented to save energy and control pollutant emissions in China have been effective in alleviating precipitation acid deposition. These findings might be used to demonstrate how developing countries could achieve economic development and environmental protection through the implementation of advanced technologies to reduce pollutant emissions.

China has become the largest coal consumer and important emitter of trace metals in the world. A multiple-year inventory of atmospheric copper (Cu) and zinc (Zn) emissions from coal combustion in 30 provinces of China and 4 economic sectors (power plant, industry sector, residential sector, and others) for the period of 1995–2014 has been calculated. The results indicated that the total emissions of Cu and Zn increased from 5137.70 t and 11484.16 t in 1995–7099.24 t and 14536.61 t in 2014, at an annual average growth rate of 1.90% and 1.33%, respectively. The industrial sector ranked as the leading source, followed by power plants, the residential use, and other sectors. The emissions of Cu and Zn were predominantly concentrated in the northern and eastern regions of China due to the enormous consumption of coal by the industrial and the power sectors. The emissions of Cu and Zn were closely associated with mortality and life expectancy (LE) on the basis of multiple regression analysis. Spatial econometric models suggested that Cu and Zn emissions displayed significantly positive relevance with mortality, while they exhibited negative correlation with LE. The influence of the Cu emission peaked in the north of China for both mortality and LE, while the impacts of the Zn emission on mortality and LE reached a maximum value in Xinjiang Province. The results of the grey prediction model suggested that the Cu emission would decrease to 5424.73 t, whereas the Zn emissions could reach 17402.13 t in 2020. Analysis of more specific data are imperative in order to estimate the emissions of both metals, to assess their human health effects, and then to adopt effective measures to prevent environmental pollution.

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0–0.10 m, or 0–0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km², with a median of 0.4 samples per km². The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis (PCA) and cluster analysis (CA).

Combined exposure to engineered nanoparticles (ENPs) and anthropogenic contaminants can lead to changes in bioavailability, uptake and thus effects of both groups of contaminants. In this study we investigated effects of single and combined exposures of silver (Ag) nanoparticles (AgNPs) and the synthetic hormone 17α-ethinylestradiol (EE2) on tissue uptake of both contaminants in juvenile turbot (Scophthalmus maximus). Silver uptake and tissue distribution (gills, liver, kidney, stomach, muscle and bile) were analyzed following a 14-day, 2-h daily pulsed exposure to AgNPs (2 μg L⁻¹ and 200 μg L⁻¹), Ag⁺ (50 μg L⁻¹), EE2 (50 ng L⁻¹) and AgNP + EE2 (2 or 200 μg L⁻¹+50 ng L⁻¹). Effects of the exposures on plasma vitellogenin (Vtg) levels, EE2 and steroid hormone concentrations were investigated. The AgNP and AgNP + EE2 exposures resulted in similar Ag concentrations in the tissues, indicating that combined exposure did not influence Ag uptake in tissues. The highest Ag concentrations were found in gills. For the Ag⁺ exposed fish, the highest Ag concentrations were measured in the liver. Our results show dissolution processes of AgNPs in seawater, indicating that the tissue concentrations of Ag may partly originate from ionic release. Plasma EE2 concentrations and Vtg induction were similar in fish exposed to the single contaminants and the mixed contaminants, indicating that the presence of AgNPs did not significantly alter EE2 uptake. Similarly, concentrations of most steroid hormones were not significantly altered due to exposures to the combined contaminants versus the single compound exposures. However, high concentrations of AgNPs in combination with EE2 caused a drop of estrone (E1) (female fish) and androstenedione (AN) (male and female fish) levels in plasma below quantification limits. Our results indicate that the interactive effects between AgNPs and EE2 are limited, with only high concentrations of AgNPs triggering synergistic effects on plasma steroid hormone concentrations in juvenile turbots.

We explored acquired immunity resulting from vaccination in 3 to 7-year-old children, chronically exposed to multiple heavy metals and metalloids, in an e-waste recycling area (Guiyu, China). Child blood levels of ten heavy metals and metalloids, including lead (Pb), arsenic (As), mercury (Hg), chromium (Cr), cadmium (Cd), manganese (Mn), nickel (Ni), copper (Cu), zinc (Zn) and selenium (Se), and seven vaccine antibodies (diphtheria, pertussis, tetanus, hepatitis B, Japanese encephalitis, polio, measles) were measured. The exposed group had higher levels of blood Pb, Mn, Cu, Zn and Cr compared to the reference group (P < 0.05). Levels of all vaccine antibodies in the exposed group were significantly lower than in the reference group (P < 0.01). All vaccine antibodies negatively correlated with blood concentrations of Cu, Zn and Pb, based on spearman rank correlation analysis. Multiple logistic regression and univariate analyses identified the location of residence (Guiyu), high blood Pb (>10 μg/dL) and high blood Cu and Zn (upper median value of each group) to be inversely associated with seven antibody titers. Antibody titers increased with age, BMI, high blood Mn (>15 μg/L), and high blood Cd and Ni (upper median value of each group). Results suggest multiple heavy metal and metalloid exposure, especially to Pb, Zn and Cu, may be a risk factor inhibiting the development of child immunity, resulting in decreased child antibody levels against vaccines.

East Asia is one of the world's largest sources of dust and anthropogenic pollution. Dust particles originating from East Asia have been recognized to travel across the Pacific to North America and beyond, thereby affecting the radiation incident on the surface as well as clouds aloft in the atmosphere. In this study, integrated analyses are performed focusing on one trans-Pacific dust episode during 12–22 March 2015, based on space-borne, ground-based observations, reanalysis data combined with Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT), and the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem). From the perspective of synoptic patterns, the location and strength of Aleutian low pressure system largely determined the eastward transport of dust plumes towards western North America. Multi-sensor satellite observations reveal that dust aerosols in this episode originated from the Taklimakan and Gobi Deserts. Moreover, the satellite observations suggest that the dust particles can be transformed to polluted particles over the East Asian regions after encountering high concentration of anthropogenic pollutants. In terms of the vertical distribution of polluted dust particles, at the very beginning, they were mainly located in the altitudes ranging from 1 km to 7 km over the source region, then ascended to 2 km–9 km over the Pacific Ocean. The simulations confirm that these elevated dust particles in the lower free troposphere were largely transported along the prevailing westerly jet stream. Overall, observations and modeling demonstrate how a typical springtime dust episode develops and how the dust particles travel over the North Pacific Ocean all the way to North America.

ZnO nanoparticles (ZnO-NPs) are emerging contaminants that raise the concerns of potential risk in the aquatic environment. It has been estimated that the environmental ZnO-NPs concentration is 76 μg/l in the aquatic environment. Our aim was to determine the aquatic toxicity of ZnO-NPs with chronic exposure at environmentally relevant concentrations using the nematode Caenorhabditis elegans. Two simulated environmentally relevant mediums—moderately hard reconstituted water (EPA water) and simulated soil pore water (SSPW)—were used to represent surface water and pore water in sediment, respectively. The results showed that the ZnO-NPs in EPA water has a much smaller hydrodynamic diameter than that in SSPW. Although the ionic release of Zn ions increased time-dependently in both mediums, the Zn ions concentrations in EPA water increased two-fold more than that in SSPW at 48 h and 72 h. The ZnO-NPs did not induce growth defects or decrease head thrashes in C. elegans in either media. However, chronic exposure to ZnO-NPs caused a significant reduction in C. elegans body bends in EPA water even with a relatively low concentration (0.05 μg/l); similar results were not observed in SSPW. Moreover, at the same concentrations (50 and 500 μg/l), body bends in C. elegans were reduced more severely in ZnO-NPs than in ZnCl2 in EPA water. The ATP levels were consistently and significantly decreased, and ROS was induced after ZnO-NPs exposure (50 and 500 μg/l) in EPA water. Our results provide evidences that chronic exposure to ZnO-NPs under environmentally relevant concentrations causes metabolic and locomotive toxicities implicating the potential ecotoxicity of ZnO-NPs at low concentrations in aquatic environments.